欢迎访问《中国农学通报》，
中国农学通报

中国农学通报 ›› 2024, Vol. 40 ›› Issue (16): 150-155.doi: 10.11924/j.issn.1000-6850.casb2023-0282

• 食品·营养·检测·安全 • 上一篇    下一篇

采用近红外光谱法无损测量樱桃品质的研究

刘佳1,2(), 李洪雯1,2, 陈丽娟1,2, 王东1,2, 张国薇1,2()   

  1. 1 四川省农业科学院园艺研究所，成都 610066
    2 农业农村部西南地区园艺作物生物学与种质创制重点实验室，成都 610066
  • 收稿日期:2023-04-12 修回日期:2024-04-13 出版日期:2024-05-30 发布日期:2024-05-30
  • 通讯作者:
    张国薇，女，1988年出生，助理研究员，主要从事果树栽培及育种技术研究。E-mail：。
  • 作者简介:

    刘佳，女，1983年出生，副研究员，主要从事果树栽培、育种、生理与分子生物学研究。E-mail：。

  • 基金资助:
    四川省农业科学院科技成果中试熟化与示范转化工程项目“科技支撑平昌县果树产业高质量发展”(2024ZSSH); 辽宁省种质创新藏粮于技专项计划(2023JH1/10200005); 中央引导地方科技发展专项科技项目“果树优良品种选育及标准化示范基地建设”(2023PSKJ); 德阳市旌阳区农业农村领域重点研发项目“果树优新品种及标准化栽培关键技术示范应用”(2024ZDYF); 四川省“十四五”果树育种攻关“突破性果树育种材料和方法创新及新品种选育”(2021YFYZ0023)

Fruit Quality Indexes Nondestructive Prediction of Cherry Using Near-infrared Spectroscopy

LIU Jia1,2(), LI Hongwen1,2, CHEN Lijuan1,2, WANG Dong1,2, ZHANG Guowei1,2()   

  1. 1 Horticulture Research Institute, Sichuan Academy of Agricultural Sciences, Chengdu 610066
    2 Southwestern Key Laboratory of Horticultural Crops Biology and Germplasm Enhancement, Ministry of Agriculture and Rural Affairs, Chengdu 610066
  • Received:2023-04-12 Revised:2024-04-13 Published:2024-05-30 Online:2024-05-30

RichHTML

5

PDF (PC)

43

摘要：

以樱桃常见品种‘雷尼尔’、‘布鲁克斯’、‘雷吉纳’、‘美早’为试材，采用近红外光谱(NIR)对可溶性固形物含量、干物质含量、果皮颜色和果实硬度4个质量指标进行无损测量，开发预测性NIR回归模型，并使用该模型测量‘雷尼尔’樱桃从果实开始着色到完全成熟阶段4个质量指标变化。结果表明，建立的可溶性固形物含量、干物质含量、果皮颜色和果实硬度模型的线性回归决定系数(R2)值分别为0.87、0.97、0.77、0.76。模型线性系数(R2)越接近1拟合效果越好，模型的拟合程度越高。R2值均大于0.7，说明模型能够达到性能预期。可溶性固形物和干物质模型进行定量测定的准确性高于果皮颜色和果实硬度模型。樱桃果实成熟阶段，可溶性固形物与干物质逐渐增加，果皮颜色逐渐加深，硬度逐渐降低。本研究建立的模型可用于其他樱桃品种品质预测，同时可为进一步探索樱桃果实成熟阶段内部物质变化提供参考依据。

关键词: 樱桃, 红外光谱, 建模, 测量, 内部品质

Abstract:

Soluble solids content, dry matter, peel color and firmness of cherry ‘Rainier’, ‘Brooks’, ‘Regina’, ‘Tieton’ were measured with no damage by near-infrared spectroscopy (NIR) in the experiment. Predictive NIR regression model was developed to measure four quality indicators using the ‘Rainier’ cherry fruit from beginning of coloration to fully maturity. The result showed that the coefficients of determination (R2) of soluble solids content, dry matter, peel color and firmness were 0.87, 0.97, 0.77 and 0.76, respectively. The closer the model linearity (R2) of the model gets to 1, the better the fitting effect and the higher the fitting degree of the model. The R2 values were all greater than 0.7, indicating that the model could achieve the performance expectations. The accuracy of the soluble solids model and dry matter model was higher than that of models of peel color and firmness. The soluble solid and dry matter gradually increased, skin color gradually deepened and hardness gradually decreased during the ripening of cherry fruit. The model established in this study can be applied in predicting four quality indexes for other cultivars, providing the intuitive reference for exploring changes on endogenous substances in the fruit ripening stage.

Key words: cherry, spectroscopy, model building, prediction, fruit quality